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S Gerassis

Showing results (1-10 of 4) with videos related to

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The Science of the Total Environment|April 12, 2024
Enhancing water quality prediction for fluctuating missing data scenarios: A dynamic Bayesian network-based processing system to monitor cyanobacteria proliferationM Pazo, S Gerassis, M Araújo, et al.
Chemosphere|December 4, 2018
A coupled multivariate statistics, geostatistical and machine-learning approach to address soil pollution in a prototypical Hg-mining site in a natural reserveC Boente, M T D Albuquerque, S Gerassis, et al.
The Science of the Total Environment|May 6, 2018
Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soilsC Boente, M T D Albuquerque, A Fernández-Braña, et al.
The Science of the Total Environment|June 19, 2017
Developing a new Bayesian Risk Index for risk evaluation of soil contaminationM T D Albuquerque, S Gerassis, C Sierra, et al.
Pageof 1

Showing results (1-10 of 4) with videos related to

Sort By:
Pageof 1
The Science of the Total Environment|April 12, 2024
Enhancing water quality prediction for fluctuating missing data scenarios: A dynamic Bayesian network-based processing system to monitor cyanobacteria proliferationM Pazo, S Gerassis, M Araújo, et al.
Chemosphere|December 4, 2018
A coupled multivariate statistics, geostatistical and machine-learning approach to address soil pollution in a prototypical Hg-mining site in a natural reserveC Boente, M T D Albuquerque, S Gerassis, et al.
The Science of the Total Environment|May 6, 2018
Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soilsC Boente, M T D Albuquerque, A Fernández-Braña, et al.
The Science of the Total Environment|June 19, 2017
Developing a new Bayesian Risk Index for risk evaluation of soil contaminationM T D Albuquerque, S Gerassis, C Sierra, et al.
Pageof 1